Cost-effectiveness of nivolumab in squamous and non-squamous non-small cell lung cancer in Canada and Sweden: an update with 5-year data
Bibliographic record
Abstract
AIMS: Nivolumab has been approved for advanced squamous and non-squamous non-small cell lung cancer (NSCLC) following platinum-based chemotherapy in both Canada and Sweden. We aimed to determine the value-for-money of nivolumab versus docetaxel in a Canadian and Swedish setting based on 5-year data. METHODS: These cost effectiveness analyses used partitioned survival models with three mutually exclusive health states: progression-free, progressed disease, and death. All clinical parameters were derived from two registration phase 3 randomized trials, CheckMate 017 and CheckMate 057, with a minimum follow-up of 5 years. Treatment duration was based on time-on-treatment data from the clinical trials. Costs were derived from published sources. The primary outcomes of the analyses were quality-adjusted life-years (QALYs), life-years gained, and incremental cost-effectiveness ratios (ICERs). The model input parameters for each analysis were chosen in line with guidance from the respective HTA authorities. RESULTS: From a Canadian payer perspective, the ICERs were CAN$140,753 per QALY in the squamous population, and CAN$173,804 per QALY in the non-squamous population, assuming a 10-year time horizon and a 5% discount rate for both costs and outcomes. Sensitivity analyses demonstrated that changes to the discount rates for outcomes had the highest impact on the ICERs. In the Swedish analysis, the ICERs were SEK568,895 per QALY in the squamous population and SEK662,991 per QALY in the non-squamous population, assuming a 15-year time horizon, a 3% discount rate, and a 2-year maximum treatment duration for nivolumab. Sensitivity analyses demonstrated that the ICERs were most sensitive to changes in the discount rate for outcomes. CONCLUSION: These updated analyses, based on more mature trial data with a minimum follow-up of 5 years, generate more favorable ICERs versus the previously submitted HTA assessments that resulted in approval of nivolumab for patients with previously treated NSCLC in Canada and Sweden.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".